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Audio transcriber tools convert spoken language from audio and video into accurate written text using automatic speech recognition (ASR). With features like automatic transcription, editing options, speaker identification, and multi-language support, these tools are essential for podcasters, journalists, business professionals, and educators. By streamlining content creation and enhancing documentation accuracy, they significantly boost productivity and improve communication in today’s digital landscape.
Convert your videos into foreign languages automatically.
Translate your videos into 125+ foreign languages by automatically: transcribing, translating, and voicing over your files in seconds.
All-in-one platform for subtitles & transcription.
HappyScribe is an Audiovisual Language Platform that helps media companies, language service providers, and corporates scale their transcription and subtitling needs efficiently. By blending advanced AI with human expertise, it enables secure team collaboration, contributor management, and rapid production of high-quality transcriptions, subtitles, and closed captions.
Turn media into social posts, blogs, newsletters, meeting notes like magic
Castmagic is an AI-powered tool that converts audio and video into transcriptions, summaries, blogs, and social media content, supporting 60+ languages with customizable outputs for different brand voices. It automates content repurposing, allowing creators to maximize engagement effortlessly.
Audio AI infrastructure for voice-first platforms.
Gladia empowers companies to utilize advanced AI for extracting actionable insights from audio data. It offers an API with exceptional speech recognition and analysis capabilities in over 100 languages. Gladia provides reliable solutions for both asynchronous and real-time transcription, along with audio intelligence services such as precise speech-to-text transcription and translation. Designed for a diverse range of users, including developers and businesses, Gladia enhances operations by tapping into the potential of audio content.
